rpact is an R package for planning, simulating, and analyzing
confirmatory clinical trials. It supports common tasks such as sample
size and power calculations for standard fixed-sample trials, as well as
classical group sequential designs with interim analyses. Methods are
available for continuous, binary, survival, and count data endpoints.
For innovative trial designs, rpact provides simulation-based
evaluation of power and other operating characteristics, multi-stage
adaptive hypothesis tests based on the combination testing principle,
adaptive sample size or event-number reassessment, multi-arm multi-stage
(MAMS) designs, and population enrichment designs. This allows users to
start with routine trial planning and use the same package for more
advanced adaptive methods when needed.
rpact covers the main steps of confirmatory trial planning,
simulation, and analysis:
- Standard fixed-sample designs without interim analyses
- Classical group sequential designs with planned interim analyses
- Sample size and power calculations for
- means (continuous endpoints)
- rates (binary endpoints)
- survival endpoints with flexible recruitment and survival-time options
- count data endpoints
- Power and operating-characteristic simulations for means, rates, survival data, and count data
- Assessment of sample size or event-number recalculations based on conditional power
- Multi-stage adaptive hypothesis testing based on the combination testing principle
- Assessment of treatment selection strategies in multi-arm trials, including multi-arm multi-stage (MAMS) settings
- Simulation and analysis methods for population enrichment designs with means, rates, and hazard ratios
- Confirmatory analysis for means, rates, and survival endpoints in one-arm, two-arm, and multi-arm trials
- Support for fixed-sample designs, classical group sequential designs, and adaptive multi-arm multi-stage (MAMS) designs based on the inverse normal or Fisher combination test
- Automatic boundary recalculation during a trial using alpha-spending approaches, including under- and over-running
Install the latest stable release from CRAN:
install.packages("rpact")To try features that are not yet available in the CRAN release, install
the development version of rpact from
GitHub:
# install.packages("pak")
pak::pak("rpact-com/rpact")The complete package documentation is available at www.rpact.org.
Step-by-step examples and tutorials are available in the rpact
vignettes at
www.rpact.org/vignettes.
If you find a bug or would like to suggest an improvement, please use
the rpact GitHub issue tracker.
-
🐞 Report a bug
Please include a minimal reproducible R example, or a runnable R Markdown (.Rmd) or Quarto (.qmd) document. -
✨ Request a feature
Please describe the use case, affected function(s), and the expected benefit.
Before opening a new issue, please search existing issues to avoid duplicates.
Because GitHub issues are public, please do not include confidential, customer-specific, personal, regulated, or security-sensitive information.
RPACT Cloud is a web-based graphical user interface for rpact. It
provides guided, browser-based access to selected rpact functionality,
including study design, sample size calculation, simulation, and
reporting, without requiring users to write R code.
RPACT Connect provides access to insights, downloads, and premium support for users and organizations working with RPACT software.
The RPACT User Group brings together users and decision-makers from
the pharmaceutical industry and CROs. Members meet regularly to exchange
experience, discuss best practices, and provide input that helps shape
the open-source development of rpact.
We invite interested users and organizations to join the community, share know-how, and contribute to the future development of statistical tools for clinical trials.
For organizations using rpact in FDA/GxP-regulated environments, RPACT
offers support and formal validation documentation for use on validated
corporate computer systems. The documentation can be customized and
licensed for exclusive use by your company to support applicable
regulatory requirements.
The validation documentation also contains the personal access data
required to perform the installation qualification with testPackage().
Contact RPACT to learn more.
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rpact is a comprehensive R package for clinical trial planning, design, simulation, and analysis.
It supports standard fixed-sample and classical group sequential designs, sample size and power calculations, simulation-based evaluation of operating characteristics, multi-stage adaptive designs, multi-arm and enrichment methods, and confirmatory trial analysis.
rpactis free of charge and open source, licensed under LGPL-3. It implements a broad range of methods described in the monograph by Wassmer and Brannath (2025).Formal validation documentation is available to customers and supporting members. For more information, visit www.rpact.com/services/sla.
For package documentation, examples, and vignettes, visit www.rpact.org.
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RPACT develops Statistical Tools for Drug Development.
We build and support open-source and commercial software solutions for clinical research, including R packages, Shiny applications, validated workflows, and cloud-based tools for trial planning, simulation, dose finding, analysis, and reporting.
RPACT is the team behind tools such as rpact, crmPack, and RPACT Cloud.
For more information, visit www.rpact.com.
